Li et al., 2020 - Google Patents
ComNet: Combinational neural network for object detection in UAV-borne thermal imagesLi et al., 2020
- Document ID
- 2719615550246953670
- Author
- Li M
- Zhao X
- Li J
- Nan L
- Publication year
- Publication venue
- IEEE Transactions on Geoscience and Remote Sensing
External Links
Snippet
We propose a deep learning-based method for object detection in UAV-borne thermal images that have the capability of observing scenes in both day and night. Compared with visible images, thermal images have lower requirements for illumination conditions, but they …
- 238000001514 detection method 0 title abstract description 103
Classifications
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
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- G—PHYSICS
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- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
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- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
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